kivy VS Keras

We will create this complete Python registration form using Kivy. We get started by installing Kivy, a powerful Python framework for building interactive applications.

For reference, YouTube runs on Python[1,2,3]:

> 1. Python and Django: YouTube’s backend is predominantly written in Python, offering a balance of performance and readability.

> 2. Google Cloud Platform...

> 3. Java and C++: YouTube also utilizes Java and C++ for specific backend services, as they provide better performance for certain tasks.

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A long time ago, I looked into these Python frameworks:

- http://www.web2py.com/

- https://kivy.org/

[1]: https://blogopost.com/youtube-tech-stack/#backend

[2]: https://medium.com/@shanthanaroja99/technology-stack-behind-...

[3]: https://youtu.be/G-lGCC4KKok

I have a multi-threaded app using Kivy for the GUI and sometimes need to update the GUI from a background thread. This app is a few years old and I recently updated to Kivy 2.2 and am now getting an exception with the message "Cannot create graphics instruction outside the main Kivy thread" -- which is related to this change in Kivy 2.1: https://github.com/kivy/kivy/pull/7270

I suggest you use kivy which is suitable for the desktop but also has the advantage of being one of few options for creating Python based native(ish) mobile apps (for IoS and Android app stores).

I think the best one right now for python is "beeware": https://beeware.org/

You also have Kivy which is prety good: https://kivy.org/

Anyone has some experience with Kivy [1]? It seems that it checks off some of my requirements, like cross-platform, supporting touch interfaces, ease of development, allows complex/fancy UIs as well, etc.

[1] https://kivy.org/

There are hot reload tools like kivy.tools.kviewer and KivyMD HotReload and I think others... but maybe they used something else, hard to tell

Notable Projects: Kivy ( https://kivy.org/ )

My name is Mathieu Virbel, and I am a consultant on system and software architecture with over 12 years of experience as a freelance and 20 years in the field. I have a passion for creating innovative and user-friendly applications. I specialize in using the open-source Kivy framework to develop desktop and mobile applications, but I am also skilled in other technologies and frameworks.

SEEKING WORK | France (UTC-1) | Remote | Full stack developer

My name is Mathieu Virbel, and I am a consultant on system and software architecture with over 12 years of experience as a freelance and 20 years in the field. I have a passion for creating innovative and user-friendly applications. I specialize in using the open-source Kivy framework to develop desktop and mobile applications, but I am also skilled in other technologies and frameworks.

I worked on a variety of subjects, from Interactives and mobile application for Museum and Public Institutions, Embedded system in security company, telecommunication, and Startups environments from scratch. Recently playing with Python, Golang, VueJS 3/Typescript, InfluxDB, Docker Swarm, as well as writing specifications and reviewing code of others contractors.

Technologies: Python (django, flask, tensorflow, Kivy, …), Golang, TypeScript, VueJS, Quasar, Docker, Docker Swarm, Terraform, Ansible, MongoDB, InfluxDB, MariaDB, SQLite, Kafka, Prometheus/Graphana

Résumé/CV: https://meltingrocks.com/cv

LinkedIn: https://www.linkedin.com/in/mathieuvirbel/

Website: https://meltingrocks.com

Email: [email protected]

Notable Projects: Kivy ( https://kivy.org/ )

After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow.

All breaking changes are listed here: https://github.com/keras-team/keras/issues/18467

You can use this migration guide to identify and fix each of these issues (and further, making your code run on JAX or PyTorch): https://keras.io/guides/migrating_to_keras_3/

I'm guessing the "real" keras code is coming from the keras repository. Is that a correct assumption? How does that version of Keras get there? If I wanted to write my own activation layer next to ELU, where exactly would I do that?

Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks.

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I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them.

Keras documentation: https://keras.io/